Evidence map›Paper›PMID 33959262›Full record

ReviewClinical kidney journal2021

Pharmacoepidemiology for nephrologists (part 2): potential biases and how to overcome them.

Edouard L Fu, Merel van Diepen, Yang Xu, Marco Trevisan, Friedo W Dekker, Carmine Zoccali, Kitty Jager, Juan Jesus Carrero

Abstract readReview
In one paragraph

Review in Clinical kidney journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

34 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Trial
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Hyperkalemia and maintenance of renin-angiotensin system inhibitor therapy after initiating SGLT-2 or DPP-4 inhibitors.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2025
    Article
  15. Article
  16. Stopping Versus Continuing Metformin in Patients With Advanced CKD: A Nationwide Scottish Target Trial Emulation Study.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2025 · on this map
    Observational
  17. When impact trials are not feasible: alternatives to study the impact of prediction models on clinical practice.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2024
    Article
  18. Article
  19. Article
  20. Antihypertensive Drug Treatment and the Risk for Intrahemodialysis Hypotension.Clinical journal of the American Society of Nephrology : CJASN · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Edouard L FuDepartment of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.ORCID https://orcid.org/0000-0002-9698-6825
Merel van DiepenDepartment of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.
Yang XuDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden.
Marco TrevisanDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden.
Friedo W DekkerDepartment of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.
Carmine ZoccaliCNR-IFC, Clinical Epidemiology of Renal Diseases and Hypertension, Reggio Calabria, Italy.
Kitty JagerDepartment of Medical Informatics, ERA-EDTA Registry, Amsterdam University Medical Center, Amsterdam Public Health Research Institute, University of Amsterdam, Amsterdam, The Netherlands.
Juan Jesus CarreroDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden.ORCID https://orcid.org/0000-0003-4763-2024

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Observational pharmacoepidemiological studies using routinely collected healthcare data are increasingly being used in the field of nephrology to answer questions on the effectiveness and safety of medications. This review discusses a number of biases that may arise in such studies and proposes solutions to minimize them during the design or statistical analysis phase. We first describe designs to handle confounding by indication (e.g. active comparator design) and methods to investigate the influence of unmeasured confounding, such as the E-value, the use of negative control outcomes and control cohorts. We next discuss prevalent user and immortal time biases in pharmacoepidemiology research and how these can be prevented by focussing on incident users and applying either landmarking, using a time-varying exposure, or the cloning, censoring and weighting method. Lastly, we briefly discuss the common issues with missing data and misclassification bias. When these biases are properly accounted for, pharmacoepidemiological observational studies can provide valuable information for clinical practice.

Indexed as

biascausal inferenceconfoundingepidemiologic methodsobservational studiespharmacoepidemiology

Identifiers

PMID33959262
PMCPMC8087121

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.